View Single Post
Old 02-20-2013, 04:18 PM
vikasatkin vikasatkin is offline
Join Date: Sep 2011
Posts: 39
Default Discussion of Lecture 13 "Validation"

Links: [Lecture 13 slides] [all slides] [Lecture 13 video]

Question: (Slide 7/22) 1. Why do we report g instead of g^{-}? 2. Why do we report E_{val}(g^{-}) instead of E_{val}(g)?

Answer: 1. Because from theoretical analysis we know, that the more points we have in the dataset the better the learning outcome is. So it is better to use N points for training, than N-K, although we can't measure, how much better it is.
2. Because we can't report E_{val}(g): we trained on all N points, so we don't have any other points to compute E_{val}(g) (we can't use some of these N points, because they are already contaminated).
Reply With Quote